mlsanityData to 7 Oct 2026

Continuous Integration, Delivery and Deployment: A Systematic Review on Approaches, Tools, Challenges and Practices

arXiv 1703.07019 ↗First posted 21 Mar 2017cs.SEcited by 22

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Abstract (arXiv)

Context: Continuous practices, i.e., continuous integration, delivery, and deployment, are the software development industry practices that enable organizations to frequently and reliably release new features and products. With the increasing interest in and literature on continuous practices, it is important to systematically review and synthesize the approaches, tools, challenges, and practices reported for adopting and implementing continuous practices. Objective: This research aimed at systematically reviewing the state of the art of continuous practices to classify approaches and tools, identify challenges and practices in this regard, and identify the gaps for future research. Method: We used systematic literature review (SLR) method for reviewing the peer-reviewed papers on continuous practices published between 2004 and 1st June 2016. We applied thematic analysis method for analysing the data extracted from reviewing 69 papers selected using predefined criteria. Results: We have identified thirty approaches and associated tools, which facilitate the implementation of continuous practices in the following ways: (1) "reducing build and test time in continuous integration (CI)"; (2) "increasing visibility and awareness on build and test results in CI"; (3) "supporting (semi-) automated continuous testing"; (4) "detecting violations, flaws and faults in CI"; (5) "addressing security and scalability issues in deployment pipeline", and (6) "improving dependability and reliability of deployment process". We have also determined a list of critical factors such as "testing (effort and time)", "team awareness and transparency", "good design principles", "customer", "highly skilled and motivated team", "application domain", and "appropriate infrastructure" that should be carefully considered when introducing continuous practices in a given organization.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Mar 2017.

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Citing papers per year: 2021: 1; 2022: 1; 2023: 5; 2024: 2; 2025: 6; 2026: 7.

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  1. 2022Robot Learning on the Job: Human-in-the-Loop Autonomy and Learning During Deploymentcited by 101
  2. 2023Towards Autonomous Testing Agents via Conversational Large Language Modelscited by 13
  3. 2024Systematic Literature Review on Application of Learning-based Approaches in Continuous Integrationcited by 6
  4. 2023SoK: Machine Learning for Continuous Integrationcited by 4
  5. 2023DialogVCS: Robust Natural Language Understanding in Dialogue System Upgradecited by 4
  6. 2026Automated Self-Testing as a Quality Gate: Evidence-Driven Release Management for LLM Applicationscited by 3
  7. 2026The End of Code Review: Coding Agents Supersede Human Inspectioncited by 3
  8. 2023Systematic Literature Review on Application of Machine Learning in Continuous Integrationcited by 2
  9. 2024Towards a Middleware for Large Language Modelscited by 2
  10. 2023Graph-Based Model-Agnostic Data Subsampling for Recommendation Systemscited by 1
  11. 2025Leveraging Reward Models for Guiding Code Review Comment Generationcited by 1
  12. 2025Foundational Models and Federated Learning: Survey, Taxonomy, Challenges and Practical Insightscited by 1
10 more
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  3. 2025Search-Based Software Engineering and AI Foundation Models: Current Landscape and Future Roadmapcited by 0
  4. 2025A Generative Approach for Semantic Auditing of Electronic Health Recordscited by 0
  5. 2025A Concept for Efficient Scalability of Automated Driving Allowing for Technical, Legal, Cultural, and Ethical Differencescited by 0
  6. 2026The Alignment Flywheel: A Governance-Centric Hybrid MAS for Architecture-Agnostic Safetycited by 0
  7. 2026CCCE: A Continuous Code Calibration Engine for Autonomous Enterprise Codebase Maintenance via Knowledge Graph Traversal and Adaptive Decision Gatingcited by 0
  8. 2026From Assistance to Agency: Rethinking Autonomy and Control in CI/CD Pipelinescited by 0
  9. 2026Latent Anchor-Driven Test Generation for Deep Neural Networkscited by 0
  10. 2026LLM-Driven CI-CD Workflow Intelligence for Cyber Systems Engineeringcited by 0